{"id":"W2907970548","doi":"10.1111/eva.12736","title":"Detailed insights into pan‐European population structure and inbreeding in wild and hatchery Pacific oysters (<i>Crassostrea gigas</i>) revealed by genome‐wide SNP data","year":2018,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Marine Bivalve and Aquaculture Studies","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Island University","funders":"Natural Environment Research Council; Seventh Framework Programme; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; European Commission; Sight Research UK","keywords":"Biology; Crassostrea; Hatchery; Inbreeding; Pacific oyster; Fishery; Population; Population genomics; Population genetics; Genome; Ecology; Genomics; Genetics; Oyster; Fish <Actinopterygii>; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001384665,0.000168986,0.0001455698,0.00004750209,0.000449995,0.00003507888,0.0002476881,0.00005739266,0.00005827976],"category_scores_gemma":[0.00002897543,0.0001513854,0.0000149561,0.0003017014,0.0003170591,0.0004291153,0.0006208238,0.0001319971,0.00003591447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00010267,"about_ca_system_score_gemma":0.000005384909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003796611,"about_ca_topic_score_gemma":0.001545497,"domain_scores_codex":[0.9987526,0.00007865505,0.0002575265,0.0005620677,0.0001658299,0.00018332],"domain_scores_gemma":[0.9993308,0.00004919494,0.0001020376,0.0004195759,0.00001393827,0.00008446078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008849492,0.000034526,0.9785081,0.0000131796,0.00001535832,7.671179e-7,0.0007457557,0.000005341133,0.01036895,0.00009620369,0.00701551,0.003187529],"study_design_scores_gemma":[0.0002155628,0.00002310682,0.9643757,0.00001198815,0.00001940937,0.00000703854,0.0003089856,0.0003038411,0.00001722101,0.002395704,0.03214094,0.0001805109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932199,0.0007434603,0.0006669158,0.001095115,0.00002736514,0.0005527321,0.00008155939,0.00005191076,0.00356111],"genre_scores_gemma":[0.9966716,0.0002384988,0.001797666,0.0001170937,0.0001161818,0.00004120419,0.0006877499,0.00001479712,0.0003151873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02512543,"threshold_uncertainty_score":0.6173318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01165855107556031,"score_gpt":0.2304073367994489,"score_spread":0.2187487857238886,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}